Wish I had the research budget to work on the intersection of SVG and ML. I feel there is a rich vein awaiting discovery apart from the semantic stuff. Compact, efficient machine representations that consume 10x less memory for large SVG images, for example.
A few years back I had the idea to morph fonts using vector graphic interpolation. Unfortunately it was a bit more complicated than I had anticipated and as usual it was abandoned in favor of newer, shinier projects. But it's still fun to play around with:
This is a standard feature of modern (variable) fonts [0]
However, they are limited to linear interpolation of the control point polygon, IIRC.
If you want arbitrary morphing (of the actual curve) you might want to look into implicit curves [1] represented in geometric algebra [2]. Here [3] is an example of it.
That's all great stuff, but my idea was rather to explore the latent space inbetween existing fonts, so to speak. V-fonts are nice but very limited. Implicit curves are cool but I don't see how they could represent existing font data?
Packing multiple different fonts into one parametrizable one is the inverse of using one parametrizable font to generate multiple different fonts, right?
>> V-fonts are nice but very limited
As I already mentioned, therefore I agree.
>> Implicit curves are cool but I don't see how they could represent existing font data?
It might not be obvious from the wikipedia page, but implicit curves are not a class of curves but a different way to formalize them (as opposed to parametric curves). So you can think of / deal with the bezier curve segments either as parametric curves or as implicit curves.
Related work from 2008: Mona Lisa in 50 polygons, using a genetic algorithm.[0][1] Sadly I think they refused to release their source, but I believe others have re-implemented it.
For example. Dave Hoskins (shadertoy)
To get the triangle look comment out #define ADD_DITHER and press the Compile (play) button.
https://www.shadertoy.com/view/MsX3WH
I was really hopping this was some chain of CV, NLP, and GANs to implement word2vec but for images. I think I just found one of my new side-projects for the year.
